---
base_model:
- sometimesanotion/Qwen2.5-14B-Vimarckoso
- CultriX/SeQwence-14B-EvolMerge
- CultriX/Qwen2.5-14B-SLERPv7
- CultriX/SeQwence-14Bv1
- qingy2019/Qwen2.5-Math-14B-Instruct
- allknowingroger/QwenSlerp6-14B
- CultriX/Qwen2.5-14B-Wernicke
- VAGOsolutions/SauerkrautLM-v2-14b-DPO
library_name: transformers
tags:
- mergekit
- merge

---
# merge

This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

## Merge Details
### Merge Method

This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [CultriX/SeQwence-14Bv1](https://huggingface.co/CultriX/SeQwence-14Bv1) as a base.

### Models Merged

The following models were included in the merge:
* [sometimesanotion/Qwen2.5-14B-Vimarckoso](https://huggingface.co/sometimesanotion/Qwen2.5-14B-Vimarckoso)
* [CultriX/SeQwence-14B-EvolMerge](https://huggingface.co/CultriX/SeQwence-14B-EvolMerge)
* [CultriX/Qwen2.5-14B-SLERPv7](https://huggingface.co/CultriX/Qwen2.5-14B-SLERPv7)
* [qingy2019/Qwen2.5-Math-14B-Instruct](https://huggingface.co/qingy2019/Qwen2.5-Math-14B-Instruct)
* [allknowingroger/QwenSlerp6-14B](https://huggingface.co/allknowingroger/QwenSlerp6-14B)
* [CultriX/Qwen2.5-14B-Wernicke](https://huggingface.co/CultriX/Qwen2.5-14B-Wernicke)
* [VAGOsolutions/SauerkrautLM-v2-14b-DPO](https://huggingface.co/VAGOsolutions/SauerkrautLM-v2-14b-DPO)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: VAGOsolutions/SauerkrautLM-v2-14b-DPO
    parameters:
      weight: 0.20  # Strong IFEval and factual reasoning baseline
      density: 0.6
  - model: allknowingroger/QwenSlerp6-14B
    parameters:
      weight: 0.20  # Balanced reasoning across multiple benchmarks
      density: 0.6
  - model: CultriX/SeQwence-14B-EvolMerge
    parameters:
      weight: 0.15  # Generalist model for BBH and MUSR
      density: 0.5
  - model: CultriX/Qwen2.5-14B-Wernicke
    parameters:
      weight: 0.15  # QA leader for GPQA and MUSR
      density: 0.6  # Increase density to preserve more QA-specific parameters
  - model: qingy2019/Qwen2.5-Math-14B-Instruct
    parameters:
      weight: 0.15  # Specialist for MATH and advanced reasoning
      density: 0.6
  - model: sometimesanotion/Qwen2.5-14B-Vimarckoso
    parameters:
      weight: 0.10  # MUSR leader for nuanced multi-step reasoning
      density: 0.5
  - model: CultriX/Qwen2.5-14B-SLERPv7
    parameters:
      weight: 0.05  # Contextual reasoning support for BBH and tiny benchmarks
      density: 0.5
base_model: CultriX/SeQwence-14Bv1
merge_method: dare_ties
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16
adaptive_merge_parameters:
  task_weights:
    IFEval: 1.3        # Enhanced instruction-following and factual tasks
    BBH: 1.3           # Strengthened complex reasoning capabilities
    MATH_Lvl_5: 1.4    # Prioritize advanced mathematical tasks
    GPQA: 1.4          # Boost graduate-level knowledge capabilities
    MuSR: 1.3          # Strengthen multi-step reasoning on complex tasks
    MMLU_PRO: 1.2      # Ensure broad domain understanding
  smoothing_factor: 0.15  # Sharper blending for reasoning and factual tasks
gradient_clipping: 0.9   # Tighter control for precise parameter scaling

```